About
Built for how
research actually works.
Our Mission
ARAS — Advanced Research Automation System — was built to solve a real problem: research teams are doing world-class science but managing their work with disconnected tools, paper notebooks, and spreadsheets that were never designed for modern lab complexity.
We believe every research team — from a single PI with two students to a full department — deserves an operating system that documents, connects, and automates the work of science, so researchers can spend more time discovering and less time managing.
What is ARAS?
ARAS is a project-centric Research Operating System. Unlike traditional LIMS or ELN products that manage single workflows, ARAS connects every layer of your research — from team identity and lab operations, through knowledge management and AI-assisted analysis, to publication output and compliance — in one unified ecosystem.
Electronic Lab Notebook
Immutable, timestamped, digitally signed — your lab's permanent scientific record.
Proactive AI Agents
Scout, Protocol Advisor, Data Analyst, Writing Agent, and Djibril — your research team's AI layer.
Role-Based Collaboration
PI, Research Associate, Graduate Student, Lab Technician — each with the right access and view.
Audit Trail & Compliance
Every action logged. Ethics tracking, data locks, and immutable records for institutional review.
Who is ARAS for?
Principal Investigator (PI)
Full project oversight, team monitoring, budget tracking, and strategic direction across all active research projects.
Research Associate
Manage ELN entries, execute protocols, review student work, and oversee day-to-day lab operations.
Graduate Student (S2/S3)
Log experiments, upload data, track thesis milestones, and access Individual Development Plans.
Undergraduate Student (S1)
Complete assigned tasks, follow SOPs, and contribute to data collection under supervision.
Lab Technician
Execute protocols step-by-step, manage inventory, and track equipment — without exposure to sensitive data.
5-Layer Architecture
ARAS is structured in five layers — from Identity & Project Core at the foundation, through Lab Operations, Knowledge & Data, the AI Agent Layer, all the way to Output & Compliance at the top. Every module is project-scoped, role-aware, and connected.
Explore the architecture